Abstract

Effective management of gas influxes during drilling for either oil-gas or geothermal wells is crucial for ensuring operational safety and minimizing non-productive times, especially for high-pressure, high-temperature (HPHT) situations. In recent years, there has been a growing demand for comprehensive modeling techniques that can accurately predict gas influx behaviors during Managed Pressure Drilling (MPD). However, many existing approaches have neglected the heat transfer processes between wellbore fluids and the surrounding formation during gas influx management, which can significantly impact the estimation accuracy.To address this issue, this paper presents an advanced transient multiphase flow and heat transfer modeling framework that integrates the solution of the energy conservation equation with the multiphase mass and momentum equations using a two-way coupled approach. A set of full-scale experimental data, including fiber-optic-based Distributed Temperature Sensing (DTS) measurements, were used to perform thorough validation and verifications of the developed modeling framework. Multiple existing heat convection correlations were benchmarked against the DTS measurements to determine the best match. The data from multi-depth downhole temperature sensors and Distributed Acoustic Sensing (DAS) were also compared to the results from numerical simulations.The estimation results of the wellbore fluids temperature profiles showed good agreement with the DTS data for both transient single-phase flow cases and gas influx management scenarios. A comparative analysis revealed that the selection of convective heat transfer correlations could significantly affect the simulation accuracy of fluid temperature distributions and gas influx behaviors. The benchmarking and optimized selection of convection correlations help to improve the performance of transient heat-transfer modeling. In addition, the two-way coupled approach shows improved accuracy compared to the decoupled methods, particularly for HPHT situations and more transient processes.

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